Subsets of Slow Dynamic Modes Reveal Global Information Sources as Allosteric Sites

Area of Science:

• Biophysics
• Structural Biology
• Computational Biology

Background:

• Allostery is a fundamental biological regulation mechanism.
• Understanding allosteric interactions is crucial for deciphering protein function and dysfunction.
• Dynamic information flow offers a novel perspective on these interactions.

Purpose of the Study:

• To develop a novel method for dissecting protein allosteric pathways using dynamic information flow.
• To identify key residues that act as global information sources and control allosteric communication.
• To explore the potential of these identified residues for structure-based drug design.

Main Methods:

• Implementation of Gaussian Network Model (GNM) based Transfer Entropy (TE) calculations.
• Dissection of dynamic information into subsets of slow dynamic modes.
• Calculation of the collectivity (Col) in information transfer (TECol score) for residues.

Main Results:

• The method reveals distinct layers of multi-directional allosteric pathways within protein structures.
• Specific residues were identified as powerful effectors and global information sources based on their TECol scores.
• These identified residues correlate with known active and allosteric sites in proteins like ATCase, Na+/K+-ATPase, and TRPM2.

Conclusions:

• The identified information source residues are critical for disseminating information and orchestrating allosteric communication.
• These residues represent promising targets for structure-based drug design.
• The novel GNM-TE approach provides a powerful tool for analyzing protein dynamics and allosteric regulation.